Introduction of olfactory cues into a virtual reality system

ABSTRACT

A virtual reality (VR) olfactory apparatus includes an odorant saturation chamber having an inlet and an outlet. At least a portion of the odorant saturation chamber includes a plurality of beads and a liquid. The liquid includes an odorant concentrate. The inlet extends into this portion of the odorant saturation chamber. The VR apparatus also includes a mass flow controller to generate an air flow to the inlet of the odorant saturation chamber such that the air flow passes through the portion of the odorant saturation chamber to form an odorant. The air flow passes the odorant through the outlet of the odorant saturation chamber. The VR apparatus further includes a nose chamber connected to the outlet and configured to receive the odorant.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims the priority benefit of U.S. ProvisionalPatent App. No. 62/670,353 filed on May 11, 2018, the entire disclosureof which is incorporated by reference herein.

GOVERNMENT LICENSE RIGHTS

This invention was made with government support under grant/award number1R01MH101297 awarded by the National Institutes of Health (NIH). Thegovernment has certain rights in the invention.

BACKGROUND

Virtual reality refers to a computer-generated simulation of athree-dimensional (3D) image or environment that a user is able tointeract with. The user can be a human or animal, depending on thesystem. The user is able to interact with the simulation via specialelectronic equipment such as a helmet or headset with a screen inside,gloves or other clothing/accessories that are fitted with sensors,actuators, etc. In addition to visual cues, a virtual reality simulationcan also be enhanced with other sensory cues to improve the userexperience. For example, sensors and/or actuators can be used to providea tactile experience for the user in conjunction with the visual cues.Additionally, speakers can be incorporated into the virtual realitysystem to provide the user with audible cues in addition to the visualcues.

SUMMARY

An illustrative virtual reality (VR) olfactory apparatus includes anodorant saturation chamber. The odorant saturation chamber includes aninlet and an outlet. At least a portion of the odorant saturationchamber includes a plurality of beads and a liquid, where the liquidincludes an odorant concentrate. The inlet extends into the portion ofthe odorant saturation chamber that includes the plurality of beads andthe liquid. The VR apparatus also includes a mass flow controllerconfigured to generate an air flow to the inlet of the odorantsaturation chamber such that the air flow passes through the portion ofthe odorant saturation chamber that includes the plurality of beads andthe liquid to form an odorant. The air flow passes the odorant throughthe outlet of the odorant saturation chamber. The VR apparatus furtherincludes a nose chamber connected to the outlet of the odorantsaturation chamber and configured to receive the odorant.

An illustrative method for providing olfactory cues in a virtual realitysystem includes determining, by a processor, a virtual velocity and avirtual bearing of a user in a virtual reality environment. The methodalso includes determining, by the processor, a future virtual locationof the user within the virtual reality environment and a time at whichthe user is to arrive at the future virtual location based at least inpart on the virtual velocity and the virtual bearing. The method furtherincludes identifying, by the processor, an odorant associated with thefuture virtual location of the user in advance of the time at which theuser is to arrive at the future virtual location within the virtualreality environment. The method further includes controlling, by theprocessor, one or more mass flow controllers to release the odorant intoa nose chamber at the time at which the user is to arrive at the futurevirtual location.

Other principal features and advantages of the invention will becomeapparent to those skilled in the art upon review of the followingdrawings, the detailed description, and the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the invention will hereafter be describedwith reference to the accompanying drawings, wherein like numeralsdenote like elements.

FIG. 1 depicts an odorant delivery system for virtual reality inaccordance with an illustrative embodiment.

FIG. 2 depicts continuous odorant delivery following a 0.5 Hz sinusoidalcommand of low and high offset in accordance with an illustrativeembodiment.

FIG. 3 depicts odorant decay based on delivery at a constant flow rateover a 100 minute period of time in accordance with an illustrativeembodiment.

FIG. 4 depicts smooth odorant spatial distributions in accordance withan illustrative embodiment.

FIG. 5 depicts noisy odorant spatial distributions relative to a lineartrack used in a simulation in accordance with an illustrativeembodiment.

FIG. 6A depicts odorant delivery without use of a position predictivealgorithm in accordance with an illustrative embodiment.

FIG. 6B depicts a window for calculating instantaneous velocity for theposition-predictive algorithm in accordance with an illustrativeembodiment.

FIG. 6C depicts odorant delivery using the position-predictive algorithmfor methyl valerate (top) and α-pinene (bottom) in accordance with anillustrative embodiment.

FIG. 6D depicts residuals of the data plotted in FIGS. 6A and 6C to bestfit lines in accordance with an illustrative embodiment.

FIG. 6E depicts an ideal noisy odorant distribution for one traversalfor methyl valerate (top) and α-pinene (bottom) in accordance with anillustrative embodiment.

FIG. 6F depicts odorant delivery using only the position-predictivealgorithm in accordance with an illustrative embodiment.

FIG. 6G depicts determination of amplitude correction based on an amountof extra flow needed to achieve a concentration rate of change togenerate an ideal odorant distribution in accordance with anillustrative embodiment.

FIG. 6H depicts odorant delivery using a combinedposition-amplitude-predictive algorithm in accordance with anillustrative embodiment.

FIG. 6I depicts the power spectra of ideal noisy odorant distributions,real noisy odorant distributions with a position-only predictivealgorithm, and real noisy odorant distributions with aposition-amplitude predictive algorithm in accordance with anillustrative embodiment.

FIG. 6J depicts histograms of the residuals between the real and idealnoisy odorant distributions with the position-amplitude-predictivealgorithm on for each traversal (n=205, gray) and for all traversalspooled in accordance with an illustrative embodiment.

FIG. 6K depicts partial cross-correlation plots between each real andideal distribution (n=205, gray) and averaged over all distributions inaccordance with an illustrative embodiment.

FIG. 7 is a flow diagram depicting operations performed by aposition-amplitude-predictive algorithm in accordance with anillustrative embodiment.

FIG. 8 is a block diagram of a computing device in communication with anetwork in accordance with an illustrative embodiment.

DETAILED DESCRIPTION

Virtual reality systems can be used for entertainment such as watching amovie, playing a video game, watching a sporting event, etc. Virtualreality systems function by immersing a user into a simulation thathe/she experiences through visual cues, tactile cues, and/or audiblecues. Olfactory cues (i.e., smells) can also be incorporated into avirtual reality system. However, as discussed herein, traditionalolfactory systems are unable to provide a continuous olfactoryexperience for an adequate duration of time. Additionally, traditionalolfactory systems are unable to change/update the olfactory cues rapidlyenough to account for traversal of a virtual reality environment by ahuman or animal.

Virtual reality systems also offer unique experimental capabilities forstudying the neural basis of animal behavior. This technology providesprecise control over the animal's sensory environment, and therefore canbe used to establish relationships between sensory features of anenvironment and the tuning properties of individual neurons that can bedifficult to discern in real-world conditions. Virtual reality enablesexperiments that are either not possible or difficult to realize in realenvironments, such as generating cue conflict stimuli, deliveringnon-natural sudden changes in stimuli at particular locations, andobserving sensory-driven behavior in isolation from other sensoryinformation, such as walls/borders, textures, self-generated odors, andvestibular cues. Importantly, behaving animals can be head-restrained inVR, allowing for the application of advanced brain recording andstimulating techniques, such as whole-cell patch clamping, two-photonimaging, and two-photon stimulation that can reveal the underlyingbehavior of circuit, cellular, and sub-cellular mechanisms.

The vast majority of virtual reality (VR) studies to date have usedvisually defined environments. Tactile and auditory VR systems have alsobeen established. However, despite the importance of odor-drivenbehaviors for mammals, few attempts have been made to fully incorporateodor into a VR system, either for entertainment purposes or forexperimental/research purposes. In some studies, olfactory cues havebeen delivered to a mouse via airflow in an on/off manner duringimmersion in different visual or multisensory VR environments in orderto create a contextual association with other stimuli. In other studies,creative use of odor trails drawn on a treadmill has been validated forstudying odor tracking in rats.

However, as discussed above, a method to control odorant concentrationas a continuous function of virtual space does not currently exist.Traditional virtual reality olfactometers operate with a delay of 0.5-1s, which is too slow to provide a reproducible and high-resolutionodorant spatial distribution. For example, rodents run at variablespeeds on the order of ˜0.5 meters/second (m/s), have sniff at rates of3-12 Hertz (Hz), and can perform odor-driven behaviors on the order of˜100 milliseconds (ms). Humans can also move at rapid speeds within a VRenvironment, which limits the ability of traditional systems to providea continuous olfactory function. Because of these limitations intraditional systems, mammalian VR experiments have been restricted tousing odor as a categorical variable. While this approach has allowedfor studying high-level cognitive processes, such as associationalmemory, it is insufficient for addressing more elementary questions ofhow the brain can represent and generate behaviors within a continuousolfactory world. To address such questions, described herein is anolfactory VR system capable of controlling odors as continuous spatialvariables. To validate this system for behavioral and neuralapplications for head-fixed mice, an olfactory virtual navigationbehavior was established that engages hippocampal place cells. Analysisof the resulting data demonstrates that an environment comprised of onlyolfactory features, combined with self-motion cues, can engagehippocampal cognitive mapping mechanisms in mammals.

To control a continuous odorant distribution across virtual spaceinvolves rapid odorant delivery/clearance relative to the timescale ofthe user's movement, which depends on the type of user and the type ofsimulation. Further, to maintain this distribution for the duration of aVR session (which can involve watching a full length movie, playing avideo game, etc.) requires consistent odorant delivery with minimaldepletion over time. To achieve these criteria, described herein is anodorant delivery system that includes the fastest available mass flowcontrollers (MFCs), the smallest tube/bottle volumes possible withoutcompromising airflow, and a rapid odorant distribution system andtechnique.

FIG. 1 depicts an odorant delivery system for virtual reality inaccordance with an illustrative embodiment. As depicted, the odorantdelivery system (or olfactometer) includes two independent odorantstreams. In alternative embodiments, fewer or additional odorant streams(and corresponding hardware) such as 1, 3, 5, 10, etc. may be used. Inone embodiment, a flow rate of 0.001-0.1 Liter/minute (L/min) is passedthrough rapid odorant saturation chambers associated with each odorant.Mass flow controllers associated with each odorant can be used tocontrol the flow rate. As shown in FIG. 1, a third carrier stream havinga flow rate of ˜0.8-1 L/min (generated by a third mass flow controller)and containing blank air is directed to a passive mixing chamber alongwith flows from the odorant saturation chambers. Alternatively, adifferent flow rate may be used for the carrier stream.

The passive mixing chamber is in fluid communication with a nose chamberthat is positioned proximate to a nose of the user. This configurationallows for the concentrations of any number of different odorants to becontrolled continuously and independently. To vary olfactory stimulationwithout varying perceived airflow, the carrier stream can be updateddynamically to maintain a constant total flow rate through the nosechamber. In one embodiment, the constant total flow rate can be 1 L/min.Alternatively, a different value may be used. The carrier stream canalso be controlled independently to simulate variation in wind flow. Torapidly clear the odorants, the nose chamber can be configured to covera nose of the user and to create a micro-environment of a known volume(e.g., 0.07 cm³ for a mouse) in which the gas volume is replaced by the1 L/min airflow every duration. In one embodiment, the duration can be 4ms, although other values may be used in different embodiments. In oneembodiment, the nose chamber is designed to not touch the nose and/orfacial hair of the user.

To overcome the problems of delivery speed and consistency in anolfactometer, mouse experiments were performed using the system of FIG.1 with two distinct odorants, methyl valerate (bubblegum smell) andα-pinene (pine smell). These odorants were used with vapor pressureshigh enough to continuously saturate the vapor phase, but low enough tonot significantly deplete the liquid phase over time (e.g., 11.2 and 4.9mm Hg at 25° C., respectively). In alternative embodiments, differentvapor pressures may be used. The rapid odorant saturation chambers weredesigned in an effort to maintain steady-state saturation of the vaporphase in each odorant stream and to generate perceptible but notoverpowering scents at the nose chamber. For each odorant path, the airstream was bubbled through 12 mL of odorant solution. For the methylvalerate odorant, the odorant solution was formed of a 1:125 ratio ofmethyl valerate to mineral oil. For the α-pinene odorant, the odorantsolution was formed of a 1:37.5 ratio of α-pinene to mineral oil. Inalternative embodiments, different ratios may be used. In otheralternative embodiments, a liquid other than mineral oil may be used toform the odorant solutions.

The odorant saturation chambers were formed as a 40 mL vial that wasfilled with beads, such as 3 mm glass beads. Two thirds of each odorantsaturation chamber was also filed with an odorant solution. Thisconfiguration increased the interaction of air with the odorant solutionfirst by bubbling in through the bottom two thirds of the chamber thatcontains the odorant solution, and then by passing through the increasedsolution surface area generated by the coated beads in the top third ofthe saturation chamber. A photo-ionization detector (PID) was used tomeasure the response time and depletion of the olfactometer (measured atthe nose chamber). When driven by 0.5-Hz sinusoids, the olfactometerdelivered odorants as continuous variables with a delay of 0.148±0.059 sfor methyl valerate and 0.183±0.070 s for α-pinene (n=300 cycles: 150low-offset and 150 high-offset). FIG. 2 depicts continuous odorantdelivery following a 0.5 Hz sinusoidal command of low and high offset inaccordance with an illustrative embodiment. These delivery rates are onthe order of a sniffing cycle for a mouse.

FIG. 3 depicts odorant decay based on delivery at a constant flow rateover a 100 minute period of time in accordance with an illustrativeembodiment. In the depiction of FIG. 3, small gaps occur where baselinemeasurements were taken to calibrate the PID used to perform themeasurements at the nose chamber. At a maximum flow rate of 0.1 L/minfor ˜100 min, the odorant concentrations decayed with time constants of242 minutes and 1027 minutes for methyl valerate and α-pinene,respectively. This means that over a typical behavioral session lengthof 30 min, the fastest-depleting odorant, methyl valerate, would bereduced in magnitude by at most 12%. The proposed odorant deliverysystem therefore includes the mechanical components capable of rapid andreliable control of odorants in VR.

The olfactometer (or odorant delivery system) of FIG. 1 was incorporatedinto a visual VR system and driven using modified VR software to accountfor the incorporation of olfactory cues. This permitted the options ofsynchronizing or desynchronizing the visual and olfactory aspects of theVR system, and also using one or the other sensory modality alone.

As known in the art, real-world odorant distributions can occur asconcentration gradients caused by molecular diffusion, as distributedbursts of high-concentration plumes caused by turbulence, or as acombination of these two resulting in concentration gradients with addednoise. Accordingly, animals have been shown to use gradient-ascentand/or sparse-searching strategies under different conditions. To allowfor the study of gradient-guided navigation, use of the system hasdemonstrated that it can generate smooth spatial distributions of methylvalerate and α-pinene across a linear track used for the simulation, asdepicted in FIG. 4. Specifically, FIG. 4 depicts smooth odorant spatialdistributions in accordance with an illustrative embodiment. Thereal-world generation of odorant plumes by air turbulence is an ongoingfocus of fluid dynamics research, making it difficult to simulateprecisely a true turbulent odorant distribution in virtual reality.However, testing demonstrated that the proposed system can generate anoisy odorant distribution, as well as turbulent-like plumes. FIG. 5depicts noisy odorant spatial distributions relative to a linear trackused in the simulation in accordance with an illustrative embodiment.

Two challenges that needed to be overcome for the precise control ofodorant distributions were: 1) mechanical delay of odorant deliverythrough the olfactometer, which is discussed above, and 2) variablelocomotion velocity of the user within the VR environment requiringrapid changes in odorant flow rates. Combined, these problems resultedin a skewed odorant spatial distribution in which the user receivedconcentrations corresponding to a previous position rather than itscurrent position. To correct for this, an algorithm was developed thatdelivered odorants based on a prediction of the future position of theuser within the VR environment. This algorithm used the instantaneousposition and velocity of the user at each update iteration (˜5 ms) of VRto predict the position at one odorant mechanical delay period in thefuture. Instantaneous velocity was calculated by averaging the previousseveral Δposition/Δtime measurements within a previously determined timewindow. In one embodiment, the time window was determined offline byminimizing the error between real and predicted position of the user.Implementing the position-predictive algorithm eliminated the skew inconcentration and tightened the odorant spatial distributions by factorsof 4.4 and 3.7 for methyl valerate and α-pinene, respectively.

FIG. 6A depicts odorant delivery without use of a position predictivealgorithm in accordance with an illustrative embodiment. In FIG. 6A, twotraversals are depicted, one toward methyl valerate and one towardα-pinene (top), and one for an entire behavioral session (bottom). FIG.6B depicts a window for calculating instantaneous velocity for theposition-predictive algorithm in accordance with an illustrativeembodiment. The data in FIG. 6B was optimized offline by minimizing theerror between real and predicted position for each odorant. FIG. 6Cdepicts odorant delivery using the position-predictive algorithm formethyl valerate (top) and α-pinene (bottom) in accordance with anillustrative embodiment. Use of the position-predictive algorithmcompensated for the mechanical delay of the system despite variablelocomotion velocity, and thus generated precisely controlled odorantconcentration gradients.

FIG. 6D depicts residuals of the data plotted in FIGS. 6A and 6C to bestfit lines in accordance with an illustrative embodiment. It is notedthat with the position-predictive algorithm off, a time lag resulted inan odorant distribution that was skewed in the opposite direction of therun, causing a bimodal distribution of residuals (gray), one mode foreach run direction, as shown in FIG. 6D. As also shown, thisdistribution was made unimodal when the position-predictive algorithmwas turned on.

The position-predictive algorithm greatly improved system performance.However, the position-predictive algorithm alone was not sufficient forprecisely controlling sharp concentration changes characteristic of anoisy odorant distribution. This was due to two additional problemsassociated with the precise control of odorant distributions. Namely, avariable relationship between the rate of change of MFC flow rate andthe resulting odorant concentration change detected at the nose chamberone odorant mechanical delay in the future. Additionally, there wasfound to be a variable odorant mechanical delay as a function of controldrive frequency. These problems, combined with the problems identifiedabove, resulted in a noisy odorant signal that did not represent thespatial frequencies of an idealized noisy distribution when only theposition-predictive algorithm was implemented.

To correct for these problems, the frequency components of the ideal(desired) concentration distributions were analyzed, the mean frequencywas calculated, and the delays (one for each odor) corresponding to thismean value were chosen. An amplitude correction was then added to thecontrol algorithm to exaggerate the odorant streamflow rates by amagnitude that is a function of the desired concentration change (i.e.,the difference between current concentration and desired concentrationone odorant mechanical delay in the future). Implementing this combinedposition-amplitude-predictive algorithm enhanced the frequencycomponents of the desired concentration distribution that theposition-only predictive algorithm could not achieve. Using thisalgorithm, the ideal noisy distributions were replicated with residualerrors of 4.3% for methyl valerate and 4.6% for α-pinene and spatialphase lags of 0.00±0.30 cm for methyl valerate and also 0.00±0.30 cm forα-pinene.

FIG. 6E depicts an ideal noisy odorant distribution for one traversalfor methyl valerate (top) and α-pinene (bottom) in accordance with anillustrative embodiment. In FIG. 6E, the scale bar=30%. FIG. 6F depictsodorant delivery using only the position-predictive algorithm inaccordance with an illustrative embodiment. FIG. 6G depictsdetermination of amplitude correction based on an amount of extra flowneeded to achieve a concentration rate of change to generate an idealodorant distribution in accordance with an illustrative embodiment. FIG.6H depicts odorant delivery using a combinedposition-amplitude-predictive algorithm in accordance with anillustrative embodiment. FIG. 6I depicts the power spectra of idealnoisy odorant distributions, real noisy odorant distributions with aposition-only predictive algorithm, and real noisy odorant distributionswith a position-amplitude predictive algorithm in accordance with anillustrative embodiment. In FIG. 6I, n=205 traversals. As shown in FIG.6I, peaks occurred at the ideal frequencies (integers 1-8 m⁻¹) with theposition-amplitude predictive algorithm on. FIG. 6J depicts histogramsof the residuals between the real and ideal noisy odorant distributionswith the position-amplitude-predictive algorithm on for each traversal(n=205, gray) and for all traversals pooled in accordance with anillustrative embodiment. FIG. 6K depicts partial cross-correlation plotsbetween each real and ideal distribution (n=205, gray) and averaged overall distributions in accordance with an illustrative embodiment.

Thus, as shown in FIGS. 6A-6K, incorporation of amplitude to develop aposition-amplitude predictive algorithm for users in a virtual realityolfactory system greatly improves the ability to timely delivery theodorants. The position-amplitude predictive algorithm was used tocontrol temporal frequencies up to 4 Hz, which translates to a spatialfrequency of up to 8 m¹ for a user traveling at a speed of 0.5 m/s.These frequencies are sufficient to simulate odorant bursts measured ina real-world behavioral chamber that occur with a duration of ˜0.25 s.Thus, the proposed system can control noisy odorant distributions andturbulent-like plumes, in addition to smooth odorant concentrationgradients.

Referring again to FIG. 1, the odorant delivery system is described inmore detail below. In alternative embodiments, different values and/ormaterials may be used. In one embodiment, to deliver odorants withspatial precision to the nose chamber, pressurized air at 20 pounds persquare inch (PSI) was run through tubing (e.g., ¼ inch nylon tubing) toa filter (or pre-filter) such as a gas purifier. From the filter, thepressurized air is split and fed into additional tubing (e.g., ¼ inchnylon tubing) to reach the three mass flow controllers (MFCs) inparallel, as shown in FIG. 1. In one embodiment, one or more of the MFCscan be Alicat MC-100SCCM-D MFCs and can have a flow rate 0-0.1 L/min.Outputs of the top and bottom MFCs (in the orientation of FIG. 1) wereconnected to tubing (e.g., 1/32 inch Teflon tubing) that extends throughthe caps of the odorant saturation chambers. Specifically, the tubingextends toward a bottom portion of the odorant saturation chambers suchthat the air flow from the MFCs is forced through liquid (i.e., odorantsolution) in the chambers.

In one embodiment, air from the top MFC bubbles into a 12-mL solution ofmethyl valerate (1:125 methyl valerate:mineral oil) and air from thebottom MFC bubbles into a 12 mL solution of α-pinene (1:37.5α-pinene:mineral oil). The odorant saturation chambers themselves can beformed from a 40-mL amber glass vial with a rubber membrane cap (or lid)that facilitates the inlet tubing from the MFC and outlet tubing. Otherthan openings to accommodate inlet tubing and outlet tubing, the cap canseal the odorant saturation chamber from the environment. In alternativeembodiments, a larger or smaller odorant saturation chamber may be used,depending on the size of the system and/or the amount of odorant to beused by the system.

The odorant saturation chambers were filled nearly to the top withsoda-lime glass beads (diameter 3 mm) to increase air bubble saturationand decrease splashing. Odorant type, concentration, and odorantsaturation chamber configuration were optimized empirically to maximizedelivery speed while minimizing odorant exhaustion overlong durations.Outlet tubing (e.g., Teflon, 0.002-inch) positioned in the caps of theodorant saturation chambers above the beads/liquid are attached to apassive mixing chamber where the odorant streams meet a stream of blankair delivered by the third MFC. In one embodiment, the third MFC can bean Alicat MC-15SLPM-D/10 M, and can have a flow rate 0-1 L/min. Thisair-odorant mixture is then led through tubing (e.g., 1/32-inch Teflontubing) to a custom-made Teflon nose chamber fully covering the nose ofthe user. In alternative embodiments, different sizes and/or types oftubing may be used in the system.

To eliminate variation in airflow, blank airflow rate was updateddynamically to maintain a constant final flow of 1 L/min. All junctionswere secured by threaded Teflon fittings reinforced with Teflon tape,and regularly passed water-immersion leak-checks. All tubing length wasminimized, and all tubing diameters were optimized to the minimumpossible without compromising MFC operation or causing backflow ofodorant solution into the MFCs (through capillary action). To preventflows in any direction but toward the nose chamber, the odorant streamflow rates were not permitted to fall below 1 mL/min during all odorantdelivery sessions, including testing and behavior.

To test the above-described system, relative odorant concentration wasmeasured using a miniature photo-ionization detector (PID) with a flowrate of 950 mL/min placed at the nose chamber. The PID signal, all MFCcommand and feedback signals, and virtual position and view angle wererecorded and synchronized at 1 kHz using a data acquisition card of acomputing system. Before each PID measurement, relative odorantconcentrations of 0 and 100% were defined as the mean of 5 s of PIDsignal at flows of 1 and 100 mL/min, respectively. Subsequentmeasurements were then normalized accordingly. Since the PID cannotsimultaneously distinguish two odorants, each PID test was performedseparately. To control for any potential variation due to PID placement,the PID was fixed rigidly to the nose chamber for all sequences ofmeasurements. To facilitate odorant clearance, inward- andoutward-facing fans were built into a ceiling of the virtual realitychamber used for the testing. At the end of each day of odorantdelivery, and between all PID measurements of different odorants, theodorant bottles were removed, submerged tubing was wiped clean, emptybottles were attached, and all MFCs were set to maximum flow rate for 30min. Fresh odorants solutions in new bottles were mixed daily from stockodorants that were stored in nitrogen gas.

To evaluate the speed of odorant delivery, each odorant MFC was drivenby a sinusoid of 0.5 Hz of low or high offset for 150 cycles. Delaybetween the command and the odorant delivery was calculated as the meanpeak-to-peak difference between the command signal and the PID signal.To characterize the speed of odorant delivery as a function of sinusoidfrequency, 10 cycles each were applied of all combinations of sinusoidsof amplitudes (10, 20, 30,40, 50, 60, 70, 80, 90, and 99) mL/min andfrequencies (0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4,4.5, and 5) Hz, and thedelay for each sinusoid was calculated. Delay was found to be relativelyamplitude-invariant at each frequency, and was thus pooled over allamplitudes and plotted as a function of frequency.

To evaluate the stability of odorant delivery, each odor MFC was left atits maximum flow rate of 100 mL/min for ˜100 min. A problem forlong-duration PID use is drift of the baseline reading. To quantify thePID signal relative to a stable baseline, baseline measurements (odorantstreamflow of 1 mL/min) were taken for 1 min every 20 min, and thesebaseline points were fitted with a second-order polynomial. Thispolynomial was then subtracted from the non-baseline points. Afterbaseline correction, time constants of depletion were calculated byfitting an exponential to the non-baseline points. It is believed thatthe methyl valerate was delivered more quickly, but also depleted morequickly because of its higher vapor pressure as compared to α-pinene.

The above-described system was integrated into a visual virtual realitysetup, and both visual and olfactory virtual realities were controlledin Matlab using a virtual reality engine with a refresh period of ˜5 ms.Flow rates were updated at each iteration of VR using Matlab to sendanalog voltages to the MFCs via a data acquisition card. To createsmooth odorant gradients across a 2 m linear track (FIG. 4), the MFCflow rates F (mL/min) were defined as functions of virtual positionx(m):

F ₁=1+(99/2)x   Equation 1:

F ₂=100−(99/2)x   Equation 2:

In each of the experimental testing sessions, the carrier stream was setto maintain a constant flow rate of 1000 mL/min, such that:

F3=1000−F ₁ −F ₂   Equation 3:

Additionally, as discussed above, both position-predictive andposition-amplitude predictive algorithms were utilized to improve thetiming of odorant delivery based on movement of a user within a VRenvironment. Development and use of the algorithms is described in moredetail below. In alternative embodiments, different values and/ortechniques may be used. To apply a position-predictive algorithm tocontrol smooth odorant gradients, the time delays measured as outlinedabove were selected using 0.5-Hz sinusoids. These delays were 0.148 sfor methyl valerate and 0.183 s for α-pinene. These were the times ittook from each command signal for each odorant to be received at thenose chamber, and therefore the times Δt in the future that thealgorithms needed to predict. Since Δt was different for each odorant,two independent algorithms were implemented to control each odorantstream in parallel. Each algorithm used first-order kinematics at eachiteration of VR to predict future position x_(f) as:

x _(f) =x ₀ +v ₀ Δt   Equation 4:

In Equation 4, x₀ is the instantaneous position and v₀ is theinstantaneous velocity of the user in the VR environment. Since the VRphysics engine used in this embodiment did not include an accelerationcomponent, no acceleration term was included in the algorithm. Inalternative embodiments, an acceleration term may be incorporated in thealgorithms to account for rate of change in the instantaneous velocity.The variable v₀ from Equation 4 was calculated as the average of thepreceding several Δx/Δt samples as follows:

$\begin{matrix}{v_{0} = {\frac{1}{w}{\sum\limits_{i = {1 - w}}^{0}\frac{x_{i} - x_{i - 1}}{t_{i} - t_{i - 1}}}}} & {{Equation}\mspace{14mu} 5}\end{matrix}$

In equation 5, w is the smoothing window measured in number ofiterations i. As it is not readily apparent how many previous iterationsshould be averaged to calculate instantaneous velocity, this parameterwas optimized offline. To do this, a standard behavior data set wascreated comprised of 10 min each of good, mediocre, and poor performance(characterized by the reward rate and distance run between rewards)chosen from the behavioral datasets at sampling rate 1 kHz. This testingset was then replayed in VR to simulate behavior in real time, and thepositions and timestamps were recorded in order to achieve the samesampling rate as the VR engine (4.9±0.1 ms). Equation 4 was appliedoffline at each time point to get each predicted position x_(f). Thiswas done for each value of w from 1 to 40. For each w, error wascalculated as the sum of the absolute differences between all predictedpositions x_(f) and their corresponding real future positions x(t₀+Δt)over all n samples as follows:

Error=Σ_(i=1) ^(n) |x _(f) −x(t ₀ +Δt)|  Equation 6:

This error was plotted as a function of w (FIG. 6B), and the optimumwindow was chosen as the w at which the minimum error occurred. Thesewindows were 9 iterations for methyl valerate and 10 iterations forα-pinene.

To test whether this algorithm reduces the error in the odorant spatialdistribution in real time, the PID was placed at the nose chamber andthe standard behavior was replayed with the position-predictivealgorithm on and off for each odorant. Fresh odorant solutions were usedfor each replay. To again control for the slow drift intrinsic to thePID, each recording was broken into 5-min blocks and normalized to thebest-fit line of PID signal vs position. These normalized blocks werethen pooled. The difference between the data and the best-fit line wascalculated as the sum of the absolute values of the residuals (FIG. 6D).Performance of the algorithm was visualized by plotting the differencesbetween the data and the best-fit line, i.e., the residuals as shown inFIG. 6D. Improvement bestowed by the algorithm was calculated as theratio of least absolute deviations with the algorithm off versus on. Toremove points during which the user was stationary (i.e., times when thealgorithm would be expected to have no effect), only points during whichthe user was moving faster than 0.1 m/s were included in these plots andcalculations.

To simulate a noisy environment, a set of 1000 ideal noisy odorantspatial distributions was created. Each concentration distribution C(x)was defined as a line plus a sum of spatial sinusoids as follows:

C(x)=ax+b+Σ _(i=1) ⁸ A _(i) sin(2πf _(i) x+Ø _(i))   Equation 7:

In equation 7, the line slope a=20% m⁻¹, line y-intercept b=30% formethyl valerate and a=−20% m⁻¹, b=70% for α-pinene. For both odorants,each sine wave amplitude A_(i) was chosen randomly from (0:6%), eachphase offset φ_(i) was chosen randomly from (0:2π) rad, and sine wavespatial frequency f_(i) was [1, 2, 3, 4, 5, 6, 7, 8] m⁻¹.

To simulate a turbulent-like environment, the track used in theexperiments was first divided into 24 bins, for a maximum plume rate of12 plumes m⁻¹. Plumes were then randomly assigned to these spatial binsaccording to the probability distributions:

P(x)=0.05+0.20×  Equation 8:

P(x)=0.45−0.20×  Equation 9:

Equation 8 is for methyl valerate and Equation 9 is for α-pinene suchthat methyl valerate plumes were more likely near x=2 m and α-pineneplumes were more likely near x=0 m. Plume concentration C(x) within abin was defined as a half-cycle of a rectified spatial sine wave asfollows:

C(x)=b+|A sin(2πfx)|  Equation 10:

In equation 10, b=30%, plume amplitude A for each plume was chosenrandomly from (0:50%), and frequency of the plume waveform f=6 m⁻¹ (1cycle/2 bins). The concentration in bins without plumes was defined asthe offset C(x)=b. For both the noisy and turbulent like distributions,the corresponding ideal flow distributions were calculated as:

$\begin{matrix}{{F(x)} = {1 + {\frac{99}{100}{C(x)}}}} & {{Equation}\mspace{14mu} 11}\end{matrix}$

This assumes essentially a 1:1 relationship between flow andconcentration at all positions, e.g., 100% odorant always corresponds tothe maximum flow of 100 mL/min. A delay Δt was then chosen as beingrepresentative of the frequency components of the concentrationdistribution. In this embodiment, 97 ms and 98 ms were used for methylvalerate and α-pinene, respectively. These values are the delayscorresponding to the mean temporal frequency of 2.25 Hz. In alternativeembodiments, different values may be used. The position-predictive timewindow for these delays was then optimized as described above. Thesewindows were 9 iterations for both odorants.

When implemented during VR, a new C(x) distribution was chosen each timethe user turned around, i.e., each time its view angle crossed 0 or πradians in any direction, with the bubblegum-ward view angle directiondefined as π/2 rad. The index of each chosen distribution and itscorresponding timestamp were saved to a file each time a turn-aroundoccurred. When replaying the standard behavior with theposition-predictive algorithm on, this method resulted in a somewhatnoisy-looking concentration distribution that did not capture thewaveforms of the ideal distribution. This implied that the assumption ofa 1:1 relationship between flow and concentration was not necessarilycorrect for fast concentration changes.

To determine the correct relationship between flow and concentration,each odor MFC was driven with a sequence of square pulses of flowamplitude ΔF upward from a baseline flow of 1 mL/min to (5, 10, 15 . . .100) mL/min, downward from a baseline of 100 mL/min to (95, 91, 87 . .. 1) mL/min, and outward from a baseline of 50 mL/min to (1, 5, 10, 15,. . . 100) mL/min, 10 pulses each, 2 s/pulse, followed by a 2 sbaseline. A change in PID signal ΔC was measured at time At after theonset of each square pulse. This was done by taking the triggeredaverage of the 10 PID signals and finding the magnitude of the PIDsignal at time Δt. All (ΔF, ΔC/Δt) pairs were plotted on the same graphfor all directions and amplitudes. These plots include both the upstrokeand down stroke of each square pulse. The regions of this plot with ΔFbetween ˜−25 and +25 mL/min showed a linear relationship. Thus, thenonlinear regions were discarded and the linear region for each odor wasfitted with a line with y-intercept zero of the form:

$\begin{matrix}{{\Delta \; F} = {m\frac{\Delta \; C}{\Delta \; t}}} & {{Equation}\mspace{14mu} 12}\end{matrix}$

The slopes m of these lines were 0.512 and 0.567 (mL/min)/(% s⁻¹) formethyl valerate and α-pinene, respectively. This is the change in flowneeded to achieve a 1% concentration change in delay time Δt. Theselinear fits were suitable for producing turbulent-like distributions,but resulted in overshoots of the ideal concentrations for the noisydistributions. To counteract this overshooting effect, these linear fitswere replaced with logistic (sigmoidal) fits with y-intercept zero (FIG.6G) of the form:

$\begin{matrix}{{{\Delta \; F} = \frac{L}{1 + e^{- {k{({\Delta \; {C/\Delta}\; t})}}}}},} & {{Equation}\mspace{14mu} 13}\end{matrix}$

where L=15 and k=0.106 for methyl valerate, and L=20 and k=0.080 forα-pinene.

Flow correction was also implemented during VR, first by replaying thestandard behavior for testing and calibration, and subsequently onlineduring user behavior. At each iteration, the predicted position x_(f)was calculated using Equation 4. The corresponding future idealconcentration C(x_(f)) from the current ideal noisy distribution waslooked up from the previously defined known distribution (Equation 7).The current ideal concentration C(x_(i)) was subtracted from C(x_(f)) toget change in concentration ΔC. The corrected flow rate ΔF′ needed toachieve the future ideal concentration was then calculated using theideal flow rate and the flow correction as:

ΔF′=F(x ₀)+ΔF   Equation 14:

This resulted in a flow rate that preemptively overshot that of theideal flow distribution and restored the frequency components of theideal concentration distribution. To quantify these differences in noisefrequencies controlled by the position-predictive vs theposition-amplitude-predictive algorithms, all periods of movement of atleast 0.5 m were selected, which is far enough to sample at least ¼ ofthe noisy distribution. For each such period, the real and ideal odorantdistributions were binned (averaged) into spatial bins of 1 cm toachieve the same spatial sampling rate, and the spatial power spectraldensity was then calculated. Over all of these runs through noisyconcentration distributions, the average power as a function of spatialfrequency was calculated for each algorithm case (FIG. 6I). To eliminateunwanted variability, the behavior and the sequence of noisydistribution choices were set to be identical for each algorithm case.

To quantify the performance of this position-amplitude-predictivealgorithm for producing noisy odorant spatial distributions, residualswere calculated between each real and ideal distribution for eachtraversal and for the entire replayed behavioral session, as shown inFIG. 6J. As the DC offset of the real odorant signal was subject to PIDdrift and odorant depletion, real and ideal traces on each traversalwere aligned by varying the real DC offset until the sum of absolutedifferences between the real and ideal curves was minimized. Residualswere then calculated. To quantify relative spatial phase between thereal and ideal odor curves, the cross-correlation between the real andideal curve for each traversal was then calculated (FIG. 6K, gray). Forpresentation, these cross-correlation curves were normalized andaveraged, as also shown in FIG. 6K. Spatial phase lag for each traversalwas defined as the peak of the cross-correlation.

FIG. 7 is a flow diagram depicting operations performed by aposition-amplitude-predictive algorithm in accordance with anillustrative embodiment. In alternative embodiments, fewer, additional,and/or different operations may be performed. Additionally, the use of aflow diagram is not meant to be limiting with respect to the order ofoperations performed. As depicted in FIG. 7, the overall processincludes online and offline operations. Offline, delays and flowcorrections are measured using a PID. Ideal concentrations and flows canbe a defined by a system operator. These values can then be fed into theonline algorithm that updates at each iteration of VR during usage by auser.

Online, user velocity was used to calculate predicted position at onedelay in the future. The ideal concentrations at this predicted positionwere looked up from the previously defined ideal concentrationdistributions. For smooth concentration gradients, no further correctionwas performed. For sharply changing concentrations at fast runningspeeds, the uncorrected ideal flows were insufficient for achieving thefuture ideal concentrations, as shown in FIG. 6F. Therefore, the futureideal concentrations were achieved by boosting the ideal flows by thepreviously determined flow corrections. These corrected flow rates weresent as voltage commands to the MFCs. The resulting odorantconcentrations are measured at the nose chamber using the PID asdescribed herein.

Thus, described herein is a virtual reality olfactory apparatus. In oneembodiment, the apparatus includes a first odorant saturation chamberand a second odorant saturation chamber. In alternative embodiments inwhich a different number odorant receptacles are used (e.g., 1, 3, 4, 5,10, 20, etc.), a different corresponding number of saturation chamberscan also be used.

The first odorant saturation chamber can include a first inlet (e.g.,hose) that is connected to the first receptacle through a lid of thefirst receptacle. The first odorant saturation chamber also includes afirst outlet (e.g., a hose) that can also extend through the cap. Atleast a portion of the first odorant saturation chamber can include afirst plurality of beads and a first liquid, and the first inlet extendsinto this portion of the first odorant saturation chamber. The firstliquid includes a first odorant concentrate. The second odorantsaturation chamber can include a second inlet (e.g., hose) that isconnected to the second receptacle through a lid of the secondreceptacle. The second odorant saturation chamber also includes a secondoutlet (e.g., a hose) that can also extend through the cap. At least aportion of the second odorant saturation chamber can include a secondplurality of beads and a second liquid, and the second inlet extendsinto this portion of the second odorant saturation chamber. The secondliquid includes a second odorant concentrate. As a result of the inletplacement, air coming into the odorant saturation chambers will bubblethrough the liquid in the chambers to form an odorant.

The apparatus also includes a first mass flow controller configured togenerate a first air flow to the first inlet of the first odorantsaturation chamber such that the first air flow passes through theportion of the first odorant saturation chamber that includes the firstplurality of beads and the first liquid to form a first odorant. Thefirst air flow passes the first odorant through the first outlet of thefirst odorant saturation chamber. Similarly, a second mass flowcontroller is configured to generate a second air flow to the secondinlet of the second odorant saturation chamber such that the second airflow passes through the portion of the second odorant saturation chamberthat includes the second plurality of beads and the second liquid toform a second odorant. The second air flow passes the second odorantthrough the second outlet of the second odorant saturation chamber. Theapparatus can also include a nose chamber connected to the first outletof the first odorant saturation chamber and the second outlet of thesecond odorant saturation chamber to receive the first and secondodorants.

The apparatus can also include a third mass flow controller in fluidcommunication with the nose chamber. The third mass flow controller isconfigured to generate a third air flow to clear or dilute the firstodorant and/or second odorant from the nose chamber. The third mass flowcontroller can further be configured to use the third air flow tomaintain a constant flow rate of air through the nose chamber.Alternatively, the flow rate can be dynamic to simulate wind, movement,or other air resistance.

The apparatus can also include a passive mixing chamber connected to thenose chamber. The passive mixing chamber can be configured to receivethe first air flow from the first outlet of the first odorant saturationchamber, the second air flow from the second mass flow controller, andthe third air flow from the third mass flow controller. In oneembodiment, a pre-filter is used to filter air used to generate thefirst air flow, the second air flow, and the third air flow.

As discussed herein, the apparatus can be used with any virtual realitysystem known in the art and configured to create a virtual realityenvironment with olfactory cues for a user. In such an embodiment, thenose chamber can be incorporated into the virtual reality system suchthat the nose chamber is positioned proximate to a nose of the user ofthe virtual reality system. The apparatus or system can includecomputing components such as a processor, memory, transceiver,interface, etc.

FIG. 8 is a block diagram of a computing device 800 in communicationwith a network 835 in accordance with an illustrative embodiment. Thecomputing device 800 can be part of a virtual reality system and/or anyother type of computing device that participates in or interacts withthe proposed system. The computing device 800 includes a processor 805,an operating system 810, a memory 815, an input/output (I/O) system 820,a network interface 825, and an olfactory cue application 830. Inalternative embodiments, the computing device 800 may include fewer,additional, and/or different components. The components of the computingdevice 800 communicate with one another via one or more buses or anyother interconnect system. The computing device 800 can be any type ofnetworked computing device such as a laptop computer, desktop computer,smart phone, tablet, gaming device, workstation, server, a music playerdevice, etc.

The processor 805 can be in electrical communication with and used tocontrol the first, second, and third mass flow controllers describedherein. Additionally, in alternative embodiments, additional mass flowcontrollers may be used to incorporate additional odors into the system.The processor 805 can also be configured to determine a virtual velocityand a virtual bearing of the user in the virtual reality environmentusing any techniques described herein or known in the art. The processor805 is also configured to determine a future virtual location of theuser within the virtual reality environment based at least in part onthe virtual velocity and the virtual bearing, as described herein.

The processor 805 is configured to identify an odorant associated withthe future virtual location of the user using the virtual realitysystem. The processor 805 also identifies the one or more mass flowcontrollers which are to be activated to form the odorant. The odorantcan include the first odorant, the second odorant, a combination of thefirst odorant and the second odorant, and/or any other combination ofodorants in embodiments that include more than two odorant saturationchambers. The processor 805 can also be configured to identify aconcentration of the odorant associated with the future virtual locationof the user using the virtual reality system, and to control theappropriate MFCs to form the proper concentration. The processor 805 canalso be configured to determine a time at which to release the odorantinto the nose chamber based at least in part on the virtual velocity ofthe user. The processor 805 can also determine a duration for which theodorant is to be maintained in the nose chamber. The duration is basedat least in part on the virtual velocity of the user. The duration mayalso be based on other occurrences in the virtual reality environment.The processor 805 can further control the third mass flow controller toremove the odorant from the nose chamber upon expiration of the durationof time. As discussed herein, the processor 805 can identify the odorantin advance of a time at which the user arrives at the future virtuallocation within the virtual reality environment.

In one embodiment, the processor 805 of the system is configured toissue one or more electronic commands to one or more of the first massflow controller, the second mass flow controller, and the third massflow controller to release the odorant and/or airflow into the nosechamber. The processor 805 also determines a time delay between issuanceof the one or more electronic commands and delivery of the odorant tothe nose chamber. The processor 805 is further configured to correct forthe time delay based at least in part on the virtual velocity of theuser such that the odorant arrives at the nose chamber at the correcttime.

The processor 805 can be any type of computer processor known in theart, and can include a plurality of processors and/or a plurality ofprocessing cores. The processor 805 can include a controller, amicrocontroller, an audio processor, a graphics processing unit, ahardware accelerator, a digital signal processor, etc. Additionally, theprocessor 805 may be implemented as a complex instruction set computerprocessor, a reduced instruction set computer processor, an x86instruction set computer processor, etc. The processor 805 is used torun the operating system 810, which can be any type of operating system.

The operating system 810 is stored in the memory 815, which is also usedto store programs, user data, network and communications data,peripheral component data, the olfactory cue application 830, and otheroperating instructions. The memory 815 can be one or more memory systemsthat include various types of computer memory such as flash memory,random access memory (RAM), dynamic (RAM), static (RAM), a universalserial bus (USB) drive, an optical disk drive, a tape drive, an internalstorage device, a non-volatile storage device, a hard disk drive (HDD),a volatile storage device, etc.

The I/O system 820 is the framework which enables users and peripheraldevices to interact with the computing device 800. The I/O system 820can include a mouse, a keyboard, one or more displays, a speaker, amicrophone, etc. that allow the user to interact with and control thecomputing device 800. The I/O system 820 also includes circuitry and abus structure to interface with peripheral computing devices such aspower sources, USB devices, data acquisition cards, peripheral componentinterconnect express (PCIe) devices, serial advanced technologyattachment (SATA) devices, high definition multimedia interface (HDMI)devices, proprietary connection devices, etc.

The network interface 825 includes transceiver circuitry that allows thecomputing device to transmit and receive data to/from other devices suchas remote computing systems, servers, websites, etc. The networkinterface 825 enables communication through a network 835, which can beone or more communication networks. The network 835 can include a cablenetwork, a fiber network, a cellular network, a wi-fi network, alandline telephone network, a microwave network, a satellite network,etc. The network interface 825 also includes circuitry to allowdevice-to-device communication such as Bluetooth® communication.

The olfactory cue application 830 can include software in the form ofcomputer-readable instructions which, upon execution by the processor805, performs any of the various operations described herein such asdetermining user velocity, determining user position, calculating afuture position, determining odorant concentration(s) for futurepositions, controlling the MFCs to release odorant and airflow, etc. Theolfactory cue application 830 can utilize the processor 805 and/or thememory 815 as discussed above. In an alternative implementation, theolfactory cue application 830 can be remote or independent from thecomputing device 800, but in communication therewith.

As discussed above, in an illustrative embodiment, any of theapparatuses or systems described herein can include and/or be incommunication with a computing system that includes, a memory,processor, user interface, transceiver, and any other computingcomponents. Any of the operations described herein may be performed bythe computing system. The operations can be stored as computer-readableinstructions on a computer-readable medium such as the computer memory.Upon execution by the processor, the computer-readable instructions areexecuted as described herein.

The word “illustrative” is used herein to mean serving as an example,instance, or illustration. Any aspect or design described herein as“illustrative” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Further, for the purposes ofthis disclosure and unless otherwise specified, “a” or “an” means “oneor more”.

The foregoing description of illustrative embodiments of the inventionhas been presented for purposes of illustration and of description. Itis not intended to be exhaustive or to limit the invention to theprecise form disclosed, and modifications and variations are possible inlight of the above teachings or may be acquired from practice of theinvention. The embodiments were chosen and described in order to explainthe principles of the invention and as practical applications of theinvention to enable one skilled in the art to utilize the invention invarious embodiments and with various modifications as suited to theparticular use contemplated. It is intended that the scope of theinvention be defined by the claims appended hereto and theirequivalents.

What is claimed is:
 1. A virtual reality olfactory apparatus comprising:a first odorant saturation chamber, wherein the first odorant saturationchamber includes a first inlet and a first outlet, wherein at least aportion of the first odorant saturation chamber includes a firstplurality of beads and a first liquid, wherein the first liquid includesa first odorant concentrate, and wherein the first inlet extends intothe portion of the first odorant saturation chamber that includes thefirst plurality of beads and the first liquid; a first mass flowcontroller configured to generate a first air flow to the first inlet ofthe first odorant saturation chamber such that the first air flow passesthrough the portion of the first odorant saturation chamber thatincludes the first plurality of beads and the first liquid to form afirst odorant, and wherein the first air flow passes the first odorantthrough the first outlet of the first odorant saturation chamber; and anose chamber connected to the first outlet of the first odorantsaturation chamber and configured to receive the first odorant.
 2. Theapparatus of claim 1, further comprising a second mass flow controllerin fluid communication with the nose chamber, wherein the second massflow controller is configured to generate a second air flow to clear ordilute the first odorant from the nose chamber.
 3. The apparatus ofclaim 2, wherein the second mass flow controller is further configuredto use the second air flow to maintain a constant flow rate of airthrough the nose chamber.
 4. The apparatus of claim 2, furthercomprising a passive mixing chamber connected to the nose chamber,wherein the passive mixing chamber is configured to receive the firstair flow from the first outlet of the first odorant saturation chamberand the second air flow from the second mass flow controller.
 5. Theapparatus of claim 2, further comprising a pre-filter configured tofilter air used to generate the first air flow and the second air flow.6. The apparatus of claim 1, further comprising a virtual reality systemconfigured to create a virtual reality environment for a user, whereinthe nose chamber is incorporated into the virtual reality system suchthat the nose chamber is positioned proximate to a nose of the user ofthe virtual reality system.
 7. The apparatus of claim 6, furthercomprising: a second odorant saturation chamber, wherein the secondodorant saturation chamber includes a second inlet and a second outlet,wherein at least a portion of the second odorant saturation chamberincludes a second plurality of beads and a second liquid, wherein thesecond liquid includes a second odorant concentrate, and wherein thesecond inlet extends into the portion of the second odorant saturationchamber that includes the second plurality of beads and the secondliquid; a second mass flow controller configured to generate a secondair flow to the second inlet of the second odorant saturation chambersuch that the second air flow passes through the portion of the secondodorant saturation chamber that includes the second plurality of beadsand the second liquid to form a second odorant, and wherein the secondair flow passes the second odorant through the second outlet of thesecond odorant saturation chamber such that the second odorant isreceived by the nose chamber.
 8. The apparatus of claim 7, furthercomprising a processor in electrical communication with the first massflow controller and the second mass flow controller, wherein theprocessor is configured to determine a virtual velocity and a virtualbearing of the user in the virtual reality environment.
 9. The apparatusof claim 8, wherein the processor is configured to determine a futurevirtual location of the user within the virtual reality environmentbased at least in part on the virtual velocity and the virtual bearing.10. The apparatus of claim 9, wherein the processor is configured toidentify an odorant associated with the future virtual location of theuser, wherein the odorant includes the first odorant, the secondodorant, or a combination of the first odorant and the second odorant.11. The apparatus of claim 10, wherein the processor is configured toidentify a concentration of the odorant associated with the futurevirtual location of the user.
 12. The apparatus of claim 10, wherein theprocessor is configured to determine a time at which to release theodorant into the nose chamber based at least in part on the virtualvelocity of the user.
 13. The apparatus of claim 10, wherein theprocessor is configured to: issue one or more electronic commands to oneor more of the first mass flow controller and the second mass flowcontroller to release the odorant into the nose chamber; determine atime delay between issuance of the one or more electronic commands anddelivery of the odorant to the nose chamber; and correct for the timedelay based at least in part on the virtual velocity of the user. 14.The apparatus of claim 10, wherein the processor identifies the odorantin advance of a time at which the user arrives at the future virtuallocation within the virtual reality environment.
 15. A method forproviding olfactory cues in a virtual reality system, the methodcomprising: determining, by a processor, a virtual velocity and avirtual bearing of a user in a virtual reality environment; determining,by the processor, a future virtual location of the user within thevirtual reality environment and a time at which the user is to arrive atthe future virtual location based at least in part on the virtualvelocity and the virtual bearing; identifying, by the processor, anodorant associated with the future virtual location of the user inadvance of the time at which the user is to arrive at the future virtuallocation within the virtual reality environment; and controlling, by theprocessor, one or more mass flow controllers to release the odorant intoa nose chamber at the time at which the user is to arrive at the futurevirtual location.
 16. The method of claim 15, wherein identifying theodorant comprises identifying a type of the odorant and a concentrationof the odorant.
 17. The method of claim 15, further comprisingdetermining, by the processor, a duration of time for which the odorantis to be maintained at the nose chamber.
 18. The method of claim 17,further comprising controlling, by the processor, a mass flow controllerto remove the odorant from the nose chamber upon expiration of theduration of time.
 19. The method of claim 15, wherein controlling theone or more mass flow controllers comprises causing at least one of theone or more mass flow controllers to pass an air flow to an inlet of anodorant saturation chamber such that the air flow passes through aliquid within the odorant saturation chamber, wherein the liquidincludes an odorant concentrate.
 20. The method of claim 15, wherein theodorant comprises a combination of a first odorant and a second odorant.